There is conventionally-known super-resolution processing for generating a higher-resolution output image from a plurality of input images. As an example of this super-resolution processing, PTL 1 discloses reconfigurable super-resolution processing in which an estimated high-resolution image is resampled by using a point spread function (PSF function), which is obtained from a camera model, to obtain low-resolution images, and a high-resolution image is repeatedly estimated such that the differences in pixel values between the low-resolution images and the original input image become small.
In the reconfigurable super-resolution processing of PTL 1, estimation of a high-resolution image is repeatedly performed, thus increasing the computational cost. On the other hand, if the number of repetitions is limited to a small number in order to reduce the computational cost, artifacts such as ghost images that would occur due to a moving object in the estimated high-resolution image cannot be reduced, thus degrading the quality of the output image.